Citrus is a globally consumed fruit with great popularity. Mandarin (Citrus reticulata cv. ‘Shatangju’) is a local variety, and its planting area and yield are the greatest regarding fruit tree planting in Guangdong Province, China. However, its resistance to Huanglongbing (HLB) is weak. After infection by HLB, the fruits cannot develop normally. In this study, four kinds of fruits were classified as HBG, XQG, ZQG, and DHG, according to the color of their peels. The metabolomes of the three abnormally colored groups (HBG, XQG, and ZQG) and the normally colored group (DHG) were compared using a UPLC-QQQ-MS-based metabolomics approach. In total, 913 metabolites were identified and classified into 23 different categories, including phenylpropanoids and flavonoids; among them, 215 (HBG, 177; XQG, 124; and ZQG, 62) metabolites showed differential accumulation in the three comparison groups (HBG/XQG/ZQG versus DHG). A total of 2 unique metabolites, O-caffeoyl maltotriose and myricetin were detected only in DHG samples. When comparing HBG with DHG, there were 109 decreased and 68 increased metabolites; comparing XQG with DHG, there were 88 decreased and 36 increased metabolites; comparing ZQG with DHG, 41 metabolites were decreased, and 21 metabolites were increased. Metabolic pathway enrichment analysis of these differential metabolites showed significant enrichment of the “phenylpropanoid biosynthesis” pathway in all comparison groups. The hierarchical cluster analysis of the differential metabolites of the four groups showed a clear grouping patterns. The relative contents of three phenylpropanoids, four flavonoids, two alkaloids, one anthocyanin, and two other metabolites were significantly different between each comparison group. This study might provide fundamental insight for the isolation and identification of functional compounds from the peels of citrus fruit infected with HLB and for in-depth research on the effect of HLB on the formation of fruits pigment and the development of HLB-resistant citrus varieties.

Background Mandarin 'Shatangju' is susceptible to Huanglongbing (HLB) and the HLB-infected fruits are small, off-flavor, and stay-green at the maturity period. To understand the relationship between pericarp color and HLB pathogen and the effect mechanism of HLB on fruit pericarp coloration, quantitative analyses of HLB bacterial pathogens and carotenoids and also the integrative analysis of metabolome and transcriptome profiles were performed in the mandarin 'Shatangju' variety with four different color fruits, whole green fruits (WGF), top-yellow and base-green fruits (TYBGF), whole light-yellow fruits (WLYF), and whole dark-yellow fruits (WDYF) that were infected with HLB. Results the HLB bacterial population followed the order WGF > TYBGF > WLYF > WDYF. And there were significant differences between each group of samples. Regarding the accumulation of chlorophyll and carotenoid, the chlorophyll-a content in WGF was the highest and in WDYF was the lowest. The content of chlorophyll-b in WGF was significantly higher than that in other three pericarps. There were significant differences in the total content of carotenoid between each group. WGF and TYBGF pericarps were low in phytoene, gamma-carotene, beta-cryptoxanthin and apocarotenal, while other kinds of carotenoids were significantly higher than those in WDYF. And WLYF was only short of apocarotenal. We comprehensively compared the transcriptome and metabolite profiles of abnormal (WGF, TYBGF and WLYF) and normal (WDYF, control) pericarps. In total, 2,880, 2,782 and 1,053 differentially expressed genes (DEGs), including 121, 117 and 43 transcription factors were identified in the three comparisons, respectively. The qRT-PCR confirmed the expression levels of genes selected from transcriptome. Additionally, a total of 77 flavonoids and other phenylpropanoid-derived metabolites were identified in the three comparisons. Most (76.65 %) showed markedly lower abundances in the three comparisons. The phenylpropanoid biosynthesis pathway was the major enrichment pathway in the integrative analysis of metabolome and transcriptome profiles. Conclusions Synthesizing the above analytical results, this study indicated that different color pericarps were associated with the reduced levels of some carotenoids and phenylpropanoids derivatives products and the down-regulation of proteins in flavonoids, phenylpropanoids derivatives biosynthesis pathway and the photosynthesis-antenna proteins.

Tea (Camellia sinensis) is an important crop that is mainly used in the food industry. This study using the metabolome and microbiome investigates the resistance factors of wild tea plant resources against tea gray blight disease, which is caused by Pestalotiopsis theae (Sawada) Steyaert. According to the interaction analysis of tea leaves and pathogenic fungus, the resistance of wild tea plant resource “R1” (Resistance 1) to tea gray blight disease was significantly higher than that of wild tea plant resource “S1” (Susceptibility 1). The difference between “R1” and “S1” in the metabolome was obvious. There were 145 metabolites that significantly changed. The phenolic acids and flavonoids were the major increased categories in “R1,” and it included 4-O-glucosyl-sinapate and petunidin-3-o-(6”-o-p-coumaroyl) rutinoside. Six metabolic pathways were significantly enriched, including aminoacyl-tRNA biosynthesis, flavone, and flavonol biosynthesis. In terms of bacteria, there was no significant difference between “S1” and “R1” in the principal component analysis (PCA). Pseudomonas was the major bacterial genus in “S1” and “R1.” In addition, each of the two resources had its own predominant genus: Cellvibirio was a predominant bacterial genus in “S1” and Candidatus_competibacter was a predominant bacterial genus in “R1.” In terms of fungi, the fungal diversity and the abundance of the two tea plant resource samples could be distinguished clearly. The fungal component of “S1” was more abundant than that of “R1” at the genus level. Toxicocladosporium was the predominant fungal genus of “S1,” and Filobasidium was the predominant fungal genus of “R1.” The relative abundance of unclassified-norank-norank-Chloroplast and Penicillium were significantly different between “S1” and “R1.” Penicillium was identified as a potential biomarker. They correlated with some metabolites enriched in “S1” or “R1,” such as L-arginine and quercetin-3-o-(2”-o-rhamnosyl) rutinoside-7-o-glucoside. Overall, phenolic acids, flavonoids, and Penicillium could be functional metabolites or microorganisms that contributed to improving the resistance of wild tea plant resources to tea gray blight disease.

Tea grey blight disease is one of the most destructive diseases that infects tea and is caused by the pathogen Pestalotiopsis theae (Sawada) Steyaert. L-theanine is a unique non-protein amino acid of the tea plant. Different concentrations of L-theanine exhibit significant inhibitory effects on the growth and sporulation ability of the pathogen causing tea grey blight disease. To understand the effect mechanism of L-theanine on P. theae, transcriptome profiling was performed on the pathogenic mycelium treated with three different concentrations of L-theanine: no L-theanine treatment (TH0), 20 mg/mL theanine treatment (TH2), and 40 mg/mL theanine treatment (TH4). The colony growths were significantly lower in the treatment with L-theanine than those without L-theanine. The strain cultured with a high concentration of L-theanine produced no spores or only a few spores. In total, 2344, 3263, and 1158 differentially expressed genes (DEGs) were detected by RNA-sequencing in the three comparisons, Th2 vs. Th0, Th4 vs. Th0, and Th4 vs. Th2, respectively. All DEGs were categorized into 24 distinct clusters. According to GO analysis, low concentrations of L-theanine primarily affected molecular functions, while high concentrations of L-theanine predominantly affected biological processes including external encapsulating structure organization, cell wall organization or biogenesis, and cellular amino acid metabolic process. Based on KEGG, the DEGs of Th2 vs. Th0 were primarily involved in pentose and glucuronate interconversions, histidine metabolism, and tryptophan metabolism. The DEGs of Th4 vs. Th0 were mainly involved in starch and sucrose metabolism, amino sugar, and nucleotide sugar metabolism. This study indicated that L-theanine has a significant impact on the growth and sporulation of the pathogen of tea grey blight disease and mainly affects amino acid metabolism, carbohydrate metabolism, and cellular structure-related biosynthesis processes of pathogenic fungi. This work provides insights into the direct control effect of L-theanine on pathogenic growth and also reveals the molecular mechanisms of inhibition of L-theanine to P. theae.